J.L. Bentley, D.D. Sleator, R.E. Tarjan, V.K. Wei. "A locally adaptive data compression algorithm", Communications of the ACM, Vol 29, No 4, April 1986, pp 320--330 Home/Search Document Not in Database Summary ACM TOC Related Articles Check |
This paper is cited in the following contexts:
Symbol Ranking Text Compression with Shannon Recodings - Fenwick (1997) (3 citations) (Correct)
....the expected probability of occurrence, with a following statistical compressor. 2. History of symbol ranking compressors Several compressors can be seen as implementing the methods of symbol ranking, but with little reference to Shannon s original work. An early example is the MTF compressor of [Bentley et al. 86] which uses words rather than individual characters as its basic compression symbols. Lelewer and Hirschberg 91] describe the use of self organising lists to store the contexts in a compressor derived from PPM. Howard and Vitter 93] also follow PPM in developing a compressor, but one which ....
J.L. Bentley, D.D. Sleator, R.E. Tarjan, V.K. Wei. "A locally adaptive data compression algorithm", Communications of the ACM, Vol 29, No 4, April 1986, pp 320--330
A Block-Sorting Lossless Data Compression Algorithm - Burrows, Wheeler (1994) (125 citations) (Correct)
....The transformation tends to group characters together so that the probability of finding a character close to another instance of the same character is increased substantially. Text of this kind can easily be compressed with fast locally adaptive algorithms, such as move to front coding [4] in combination with Huffman or arithmetic coding. Briefly, our algorithm transforms a string S of N characters by forming the N rotations (cyclic shifts) of S, sorting them lexicographically, and extracting the last character of each of the rotations. A string L is formed from these characters, ....
....number of a few distinct characters. The overall effect is that the probability that given character ch will occur at a given point in L is very high if ch occurs near that point in L, and is low otherwise. This property is exactly the one needed for effective compression by a move tofront coder [4], which encodes an instance of character ch by the count of distinct characters seen since the next previous occurrence of ch. When applied to the string L, the output of a move to front coder will be dominated by low numbers, which can be efficiently encoded with a Huffman or arithmetic coder. ....
J.L. Bentley, D.D. Sleator, R.E. Tarjan, and V.K. Wei. A locally adaptive data compression algorithm. Communications of the ACM, Vol. 29, No. 4, April 1986, pp. 320--330.
Symbol Ranking Text Compression - Fenwick (1996) (1 citation) (Correct)
No context found.
J.L. Bentley, D.D. Sleator, R.E. Tarjan, V.K. Wei. "A locally adaptive data compression algorithm", Communications of the ACM, Vol 29, No 4, April 1986, pp 320--330
Block Sorting Text Compression - Final Report - Fenwick (1996) (8 citations) (Correct)
No context found.
J.L. Bentley, D.D. Sleator, R.E. Tarjan, V.K. Wei. "A locally adaptive data compression algorithm", Communications of the ACM, Vol 29, No 4, April 1986, pp 320--330
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